5 citations · 6 across the 4 of their papers we have counts for
4 papers
Estimating Environmental Cost Throughout Model's Adaptive Life Cycle
Vishwesh Sangarya, Richard Bradford, Jung-Eun Kim
With the rapid increase in the research, development, and application of neural networks in the current era, there is a proportional increase in the energy needed to train and use…
Aggregate Representation Measure for Predictive Model Reusability
Vishwesh Sangarya, Richard Bradford, Jung-Eun Kim
In this paper, we propose a predictive quantifier to estimate the retraining cost of a trained model in distribution shifts. The proposed Aggregated Representation Measure (ARM) qu…
Cooperative Learning for Cost-Adaptive Inference
Xingli Fang, Richard Bradford, Jung-Eun Kim
We propose a cooperative training framework for deep neural network architectures that enables the runtime network depths to change to satisfy dynamic computing resource requiremen…
TaskShuffler++: Real-Time Schedule Randomization for Reducing Worst-Case Vulnerability to Timing Inference Attacks
Man-Ki Yoon, Jung-Eun Kim, Richard Bradford +1
This paper presents a schedule randomization algorithm that reduces the vulnerability of real-time systems to timing inference attacks which attempt to learn the timing of task exe…